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from IPython.display import Image
from IPython.display import display
from skimage import io
import sys
import os
os.chdir("/home/dev/software/fast-rcnn/tools/")
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import _init_paths
from fast_rcnn.config import cfg
from fast_rcnn.test import im_detect
from utils.timer import Timer
from utils.cython_nms import nms
import matplotlib.pyplot as plt
import numpy as np
import scipy.io as sio
import caffe, os, sys, cv2
import argparse
import dlib
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CLASSES = ('__background__','n02958343','n02769748')
NETS = {'vgg16': ('VGG16',
'vgg16_fast_rcnn_iter_40000.caffemodel'),
'vgg_cnn_m_1024': ('VGG_CNN_M_1024',
'vgg_cnn_m_1024_fast_rcnn_iter_40000.caffemodel'),
'caffenet': ('CaffeNet',
'caffenet_fast_rcnn_iter_40000.caffemodel')}
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def vis_detections(im, class_name, dets, thresh=0.5):
"""Draw detected bounding boxes."""
inds = np.where(dets[:, -1] >= thresh)[0]
if len(inds) == 0:
print 'inds 0 ?'
return
im = im[:, :, (2, 1, 0)]
fig, ax = plt.subplots(figsize=(12, 12))
ax.imshow(im, aspect='equal')
for i in inds:
bbox = dets[i, :4]
score = dets[i, -1]
ax.add_patch(
plt.Rectangle((bbox[0], bbox[1]),
bbox[2] - bbox[0],
bbox[3] - bbox[1], fill=False,
edgecolor='red', linewidth=3.5)
)
ax.text(bbox[0], bbox[1] - 2,
'{:s} {:.3f}'.format(class_name, score),
bbox=dict(facecolor='blue', alpha=0.5),
fontsize=14, color='white')
ax.set_title(('{} detections with '
'p({} | box) >= {:.1f}').format(class_name, class_name,
thresh),
fontsize=14)
plt.axis('off')
plt.tight_layout()
plt.draw()
plt.savefig("test.png")
display(Image(filename='test.png',width=400, height=400))
def run_dlib_selective_search(image_name):
if 'http://' in image_name:
img = io.imread(image_name)
else:
img = io.imread(image_name)
rects = []
dlib.find_candidate_object_locations(img,rects,min_size=50)
proposals = []
for k,d in enumerate(rects):
templist = [d.left(),d.top(),d.right(),d.bottom()]
proposals.append(templist)
proposals = np.array(proposals)
return proposals
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def demo(net, image_name):
"""Detect object classes in an image using pre-computed object proposals."""
# Load the demo image
if 'http://' in image_name:
im = io.imread(image_name)
im_file = image_name
else:
im_file = os.path.join(cfg.DATA_DIR, image_name)
im = cv2.imread(im_file)
# Load pre-computed Selected Search object proposals
# im_file = os.path.join(cfg.ROOT_DIR, 'data', 'demo', image_name + '.jpg')
obj_proposals = run_dlib_selective_search(im_file)
# Detect all object classes and regress object bounds
timer = Timer()
timer.tic()
scores, boxes = im_detect(net, im, obj_proposals)
timer.toc()
print ('Detection took {:.3f}s for '
'{:d} object proposals').format(timer.total_time, boxes.shape[0])
# Visualize detections for each class
CONF_THRESH = 0.8
NMS_THRESH = 0.3
for cls_ind, cls in enumerate(CLASSES[1:]):
cls_ind += 1 # because we skipped background
cls_boxes = boxes[:, 4*cls_ind:4*(cls_ind + 1)]
cls_scores = scores[:, cls_ind]
keep = np.where(cls_scores >= CONF_THRESH)[0]
cls_boxes = cls_boxes[keep, :]
cls_scores = cls_scores[keep]
dets = np.hstack((cls_boxes,
cls_scores[:, np.newaxis])).astype(np.float32)
keep = nms(dets, NMS_THRESH)
dets = dets[keep, :]
print 'All {} detections with p({} | box) >= {:.1f}'.format(cls, cls,
CONF_THRESH)
vis_detections(im, cls, dets, thresh=CONF_THRESH)
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prototxt = '/home/dev/software/fast-rcnn/models/VGG16/test.prototxt'
caffemodel = '/home/dev/software/fast-rcnn/data/fast_rcnn_models/vgg16_fast_rcnn_iter_40000.caffemodel'
caffe.set_mode_gpu()
caffe.set_device(6)
cfg.GPU_ID = 6
print prototxt
print caffemodel
net = caffe.Net(prototxt, caffemodel, caffe.TEST)
print '\n\nLoaded network {:s}'.format(caffemodel)
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http://image.gsshop.com/image/10/56/10567540_L1.jpg
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def select_dir(dir_name):
cfg.DATA_DIR = os.path.join(PATH_DIR, dir_name)
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PATH_DIR = '/home/dev/jude/data/ILSVRC2015_DET_sample/data/Images/ILSVRC2013_train/'
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select_dir('n02958343')
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demo(net, 'n02958343_50699.JPEG')
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demo(net, 'n02958343_14698.JPEG')
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demo(net, 'n02769748_28025.JPEG')
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demo(net, 'http://image.gsshop.com/image/10/56/10567540_L1.jpg')
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demo(net, 'http://image.gsshop.com/image/20/56/20560427_O1.jpg')
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demo(net, 'http://image.gsshop.com/image/19/19/19190021_O1.jpg')
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demo(net, 'http://image.gsshop.com/image/17/24/17245941_O1.jpg')
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demo(net, 'IMG_1275.JPEG')
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